|By Tony Baer||
|November 1, 2012 10:00 AM EDT||
With Strata, IBM IOD, and Teradata Partners conferences all occurring this week, it’s not surprising that this is a big week for Hadoop-related announcements. The common thread of announcements is essentially, “We know that Hadoop is not known for performance, but we’re getting better at it, and we’re going to make it look more like SQL.” In essence, Hadoop and SQL worlds are converging, and you’re going to be able to perform interactive BI analytics on it.
The opportunity and challenge of Big Data from new platforms such as Hadoop is that it opens a new range of analytics. On one hand, Big Data analytics have updated and revived programmatic access to data, which happened to be the norm prior to the advent of SQL. There are plenty of scenarios where taking programmatic approaches are far more efficient, such as dealing with time series data or graph analysis to map many-to-many relationships.
It also leverages in-memory data grids such as Oracle Coherence, IBM WebSphere eXtreme Scale, GigaSpaces and others, and, where programmatic development (usually in Java) proved more efficient for accessing highly changeable data for web applications where traditional paths to the database would have been I/O-constrained. Conversely Advanced SQL platforms such as Greenplum and Teradata Aster have provided support for MapReduce-like programming because, even with structured data, sometimes using a Java programmatic framework is a more efficient way to rapidly slice through volumes of data.
Until now, Hadoop has not until now been for the SQL-minded. The initial path was, find someone to do data exploration inside Hadoop, but once you’re ready to do repeatable analysis, ETL (or ELT) it into a SQL data warehouse. That’s been the pattern with Oracle Big Data Appliance (use Oracle loader and data integration tools), and most Advanced SQL platforms; most data integration tools provide Hadoop connectors that spawn their own MapReduce programs to ferry data out of Hadoop. Some integration tool providers, like Informatica, offer tools to automate parsing of Hadoop data. Teradata Aster and Hortonworks have been talking up the potentials of HCatalog, in actuality an enhanced version of Hive with RESTful interfaces, cost optimizers, and so on, to provide a more SQL friendly view of data residing inside Hadoop.
But when you talk analytics, you can’t simply write off the legions of SQL developers that populate enterprise IT shops. And beneath the veneer of chaos, there is an implicit order to most so-called “unstructured” data that is within the reach programmatic transformation approaches that in the long run could likely be automated or packaged inside a tool.
At Ovum, we have long believed that for Big Data to crossover to the mainstream enterprise, that it must become a first-class citizen with IT and the data center. The early pattern of skunk works projects, led by elite, highly specialized teams of software engineers from Internet firms to solve Internet-style problems (e.g., ad placement, search optimization, customer online experience, etc.) are not the problems of mainstream enterprises. And neither is the model of recruiting high-priced talent to work exclusively on Hadoop sustainable for most organizations; such staffing models are not sustainable for mainstream enterprises. It means that Big Data must be consumable by the mainstream of SQL developers.
Making Hadoop more SQL-like is hardly new
Hive and Pig became Apache Hadoop projects because of the need for SQL-like metadata management and data transformation languages, respectively; HBase emerged because of the need for a table store to provide a more interactive face – although as a very sparse, rudimentary column store, does not provide the efficiency of an optimized SQL database (or the extreme performance of some columnar variants). Sqoop in turn provides a way to pipeline SQL data into Hadoop, a use case that will grow more common as organizations look to Hadoop to provide scalable and cheaper storage than commercial SQL. While these Hadoop subprojects that did not exactly make Hadoop look like SQL, they provided building blocks from which many of this week’s announcements leverage.
Progress marches on
One train of thought is that if Hadoop can look more like a SQL database, more operations could be performed inside Hadoop. That’s the theme behind Informatica’s long-awaited enhancement of its PowerCenter transformation tool to work natively inside Hadoop. Until now, PowerCenter could extract data from Hadoop, but the extracts would have to be moved to a staging server where the transformation would be performed for loading to the familiar SQL data warehouse target. The new offering, PowerCenter Big Data Edition, now supports an ELT pattern that uses the power of MapReduce processes inside Hadoop to perform transformations. The significance is that PowerCenter users now have a choice: load the transformed data to HBase, or continue loading to SQL.
There is growing support for packaging Hadoop inside a common hardware appliance with Advanced SQL. EMC Greenplum was the first out of gate with DCA (Data Computing Appliance) that bundles its own distribution of Apache Hadoop (not to be confused with Greenplum MR, a software only product that is accompanied by a MapR Hadoop distro).
Teradata Aster has just joined the fray with Big Analytics Appliance, bundling the Hortonworks Data Platform Hadoop; this move was hardly surprising given their growing partnership around HCatalog, an enhancement of the SQL-like Hive metadata layer of Hadoop that adds features such as a cost optimizer and RESTful interfaces that make the metadata accessible without the need to learn MapReduce or Java. With HCatalog, data inside Hadoop looks like another Aster data table.
Not coincidentally, there is a growing array of analytic tools that are designed to execute natively inside Hadoop. For now they are from emerging players like Datameer (providing a spreadsheet-like metaphor; which just announced an app store-like marketplace for developers), Karmasphere (providing an application develop tool for Hadoop analytic apps), or a more recent entry, Platfora (which caches subsets of Hadoop data in memory with an optimized, high performance fractal index).
Yet, even with Hadoop analytic tooling, there will still be a desire to disguise Hadoop as a SQL data store, and not just for data mapping purposes. Hadapt has been promoting a variant where it squeezes SQL tables inside HDFS file structures – not exactly a no-brainer as it must shoehorn tables into a file system with arbitrary data block sizes. Hadapt’s approach sounds like the converse of object-relational stores, but in this case, it is dealing with a physical rather than a logical impedance mismatch.
Hadapt promotes the ability to query Hadoop directly using SQL. Now, so does Cloudera. It has just announced Impala, a SQL-based alternative to MapReduce for querying the SQL-like Hive metadata store, supporting most but not all forms of SQL processing (based on SQL 92; Impala lacks triggers, which Cloudera deems low priority). Both Impala and MapReduce rely on parallel processing, but that’s where the similarity ends. MapReduce is a blunt instrument, requiring Java or other programming languages; it splits a job into multiple, concurrently, pipelined tasks where, at each step along the way, reads data, processes it, and writes it back to disk and then passes it to the next task.
Conversely, Impala takes a shared nothing, MPP approach to processing SQL jobs against Hive; using HDFS, Cloudera claims roughly 4x performance against MapReduce; if the data is in HBase, Cloudera claims performance multiples up to a factor of 30. For now, Impala only supports row-based views, but with columnar (on Cloudera’s roadmap), performance could double. Cloudera plans to release a real-time query (RTQ) offering that, in effect, is a commercially supported version of Impala.
By contrast, Teradata Aster and Hortonworks promote a SQL MapReduce approach that leverages HCatalog, an incubating Apache project that is a superset of Hive that Cloudera does not currently include in its roadmap. For now, Cloudera claims bragging rights for performance with Impala; over time, Teradata Aster will promote the manageability of its single appliance, and with the appliance has the opportunity to counter with hardware optimization.
The road to SQL/programmatic convergence
Either way – and this is of interest only to purists – any SQL extension to Hadoop will be outside the Hadoop project. But again, that’s an argument for purists. What’s more important to enterprises is getting the right tool for the job – whether it is the flexibility of SQL or raw power of programmatic approaches.
SQL convergence is the next major battleground for Hadoop. Cloudera is for now shunning HCatalog, an approach backed by Hortonworks and partner Teradata Aster. The open question is whether Hortonworks can instigate a stampede of third parties to overcome Cloudera’s resistance. It appears that beyond Hive, the SQL face of Hadoop will become a vendor-differentiated layer.
Part of conversion will involve a mix of cross-training and tooling automation. Savvy SQL developers will cross train to pick up some of the Java- or Java-like programmatic frameworks that will be emerging. Tooling will help lower the bar, reducing the degree of specialized skills necessary.
And for programming frameworks, in the long run, MapReduce won’t be the only game in town. It will always be useful for large-scale jobs requiring brute force, parallel, sequential processing. But the emerging YARN framework, which deconstructs MapReduce to generalize the resource management function, will provide the management umbrella for ensuring that different frameworks don’t crash into one another by trying to grab the same resources. But YARN is not yet ready for primetime – for now it only supports the batch job pattern of MapReduce. And that means that YARN is not yet ready for Impala or vice versa.
Of course, mainstreaming Hadoop – and Big Data platforms in general – is more than just a matter of making it all look like SQL. Big Data platforms must be manageable and operable by the people who are already in IT; they will need some new skills and grow accustomed to some new practices (like exploratory analytics), but the new platforms must also look and act familiar enough. Not all announcements this week were about SQL; for instance, MapR is throwing a gauntlet to the Apache usual suspects by extending its management umbrella beyond the proprietary NFS-compatible file system that is its core IP to the MapReduce framework and HBase, making a similar promise of high performance.
On the horizon, EMC Isilon and NetApp are proposing alternatives promising a more efficient file system but at the “cost” of separating the storage from the analytic processing. And at some point, the Hadoop vendor community will have to come to grips with capacity utilization issues, because in the mainstream enterprise world, no CFO will approve the purchase of large clusters or grids that get only 10 – 15 percent utilization. Keep an eye on VMware’s Project Serengeti.
They must be good citizens in data centers that need to maximize resource (e.g., virtualization, optimized storage); must comply with existing data stewardship policies and practices; and must fully support existing enterprise data and platform security practices. These are all topics for another day.
You may also be interested in:
- Making Hadoop safe for clusterphobics
- Fast data hits the big data fast lane
- EMC's Hadoop strategy cuts to the chase
- Big data consolidation race enters home stretch, as Teradata buys Aster Data
- Oracle fills another gap in its big data offering
- VMforce: Cloud mates with Java marriage of necessity for VMware and Salesforce.com
- HP buys Fortify, and it's about time
Growth hacking is common for startups to make unheard-of progress in building their business. Career Hacks can help Geek Girls and those who support them (yes, that's you too, Dad!) to excel in this typically male-dominated world. Get ready to learn the facts: Is there a bias against women in the tech / developer communities? Why are women 50% of the workforce, but hold only 24% of the STEM or IT positions? Some beginnings of what to do about it! In her Day 2 Keynote at 17th Cloud Expo, Sandy Carter, IBM General Manager Cloud Ecosystem and Developers, and a Social Business Evangelist, wil...
Dec. 1, 2015 05:00 AM EST Reads: 619
PubNub has announced the release of BLOCKS, a set of customizable microservices that give developers a simple way to add code and deploy features for realtime apps.PubNub BLOCKS executes business logic directly on the data streaming through PubNub’s network without splitting it off to an intermediary server controlled by the customer. This revolutionary approach streamlines app development, reduces endpoint-to-endpoint latency, and allows apps to better leverage the enormous scalability of PubNub’s Data Stream Network.
Dec. 1, 2015 05:00 AM EST Reads: 357
Apps and devices shouldn't stop working when there's limited or no network connectivity. Learn how to bring data stored in a cloud database to the edge of the network (and back again) whenever an Internet connection is available. In his session at 17th Cloud Expo, Ben Perlmutter, a Sales Engineer with IBM Cloudant, demonstrated techniques for replicating cloud databases with devices in order to build offline-first mobile or Internet of Things (IoT) apps that can provide a better, faster user experience, both offline and online. The focus of this talk was on IBM Cloudant, Apache CouchDB, and ...
Dec. 1, 2015 04:45 AM EST Reads: 455
I recently attended and was a speaker at the 4th International Internet of @ThingsExpo at the Santa Clara Convention Center. I also had the opportunity to attend this event last year and I wrote a blog from that show talking about how the “Enterprise Impact of IoT” was a key theme of last year’s show. I was curious to see if the same theme would still resonate 365 days later and what, if any, changes I would see in the content presented.
Dec. 1, 2015 03:00 AM EST Reads: 468
Cloud computing delivers on-demand resources that provide businesses with flexibility and cost-savings. The challenge in moving workloads to the cloud has been the cost and complexity of ensuring the initial and ongoing security and regulatory (PCI, HIPAA, FFIEC) compliance across private and public clouds. Manual security compliance is slow, prone to human error, and represents over 50% of the cost of managing cloud applications. Determining how to automate cloud security compliance is critical to maintaining positive ROI. Raxak Protect is an automated security compliance SaaS platform and ma...
Dec. 1, 2015 03:00 AM EST Reads: 469
Most of the IoT Gateway scenarios involve collecting data from machines/processing and pushing data upstream to cloud for further analytics. The gateway hardware varies from Raspberry Pi to Industrial PCs. The document states the process of allowing deploying polyglot data pipelining software with the clear notion of supporting immutability. In his session at @ThingsExpo, Shashank Jain, a development architect for SAP Labs, discussed the objective, which is to automate the IoT deployment process from development to production scenarios using Docker containers.
Dec. 1, 2015 01:15 AM EST Reads: 124
Countless business models have spawned from the IaaS industry – resell Web hosting, blogs, public cloud, and on and on. With the overwhelming amount of tools available to us, it's sometimes easy to overlook that many of them are just new skins of resources we've had for a long time. In his general session at 17th Cloud Expo, Harold Hannon, Sr. Software Architect at SoftLayer, an IBM Company, broke down what we have to work with, discussed the benefits and pitfalls and how we can best use them to design hosted applications.
Nov. 30, 2015 03:45 PM EST Reads: 111
We all know that data growth is exploding and storage budgets are shrinking. Instead of showing you charts on about how much data there is, in his General Session at 17th Cloud Expo, Scott Cleland, Senior Director of Product Marketing at HGST, showed how to capture all of your data in one place. After you have your data under control, you can then analyze it in one place, saving time and resources.
Nov. 30, 2015 03:15 PM EST Reads: 250
The Internet of Things (IoT) is growing rapidly by extending current technologies, products and networks. By 2020, Cisco estimates there will be 50 billion connected devices. Gartner has forecast revenues of over $300 billion, just to IoT suppliers. Now is the time to figure out how you’ll make money – not just create innovative products. With hundreds of new products and companies jumping into the IoT fray every month, there’s no shortage of innovation. Despite this, McKinsey/VisionMobile data shows "less than 10 percent of IoT developers are making enough to support a reasonably sized team....
Nov. 30, 2015 03:00 PM EST Reads: 495
Just over a week ago I received a long and loud sustained applause for a presentation I delivered at this year’s Cloud Expo in Santa Clara. I was extremely pleased with the turnout and had some very good conversations with many of the attendees. Over the next few days I had many more meaningful conversations and was not only happy with the results but also learned a few new things. Here is everything I learned in those three days distilled into three short points.
Nov. 30, 2015 02:00 PM EST Reads: 373
DevOps is about increasing efficiency, but nothing is more inefficient than building the same application twice. However, this is a routine occurrence with enterprise applications that need both a rich desktop web interface and strong mobile support. With recent technological advances from Isomorphic Software and others, rich desktop and tuned mobile experiences can now be created with a single codebase – without compromising functionality, performance or usability. In his session at DevOps Summit, Charles Kendrick, CTO and Chief Architect at Isomorphic Software, demonstrated examples of com...
Nov. 30, 2015 01:45 PM EST Reads: 438
As organizations realize the scope of the Internet of Things, gaining key insights from Big Data, through the use of advanced analytics, becomes crucial. However, IoT also creates the need for petabyte scale storage of data from millions of devices. A new type of Storage is required which seamlessly integrates robust data analytics with massive scale. These storage systems will act as “smart systems” provide in-place analytics that speed discovery and enable businesses to quickly derive meaningful and actionable insights. In his session at @ThingsExpo, Paul Turner, Chief Marketing Officer at...
Nov. 30, 2015 01:45 PM EST Reads: 440
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu’s platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
Nov. 30, 2015 01:00 PM EST Reads: 542
In his General Session at 17th Cloud Expo, Bruce Swann, Senior Product Marketing Manager for Adobe Campaign, explored the key ingredients of cross-channel marketing in a digital world. Learn how the Adobe Marketing Cloud can help marketers embrace opportunities for personalized, relevant and real-time customer engagement across offline (direct mail, point of sale, call center) and digital (email, website, SMS, mobile apps, social networks, connected objects).
Nov. 30, 2015 12:45 PM EST Reads: 346
The Internet of Everything is re-shaping technology trends–moving away from “request/response” architecture to an “always-on” Streaming Web where data is in constant motion and secure, reliable communication is an absolute necessity. As more and more THINGS go online, the challenges that developers will need to address will only increase exponentially. In his session at @ThingsExpo, Todd Greene, Founder & CEO of PubNub, exploreed the current state of IoT connectivity and review key trends and technology requirements that will drive the Internet of Things from hype to reality.
Nov. 30, 2015 10:45 AM EST Reads: 466
Two weeks ago (November 3-5), I attended the Cloud Expo Silicon Valley as a speaker, where I presented on the security and privacy due diligence requirements for cloud solutions. Cloud security is a topical issue for every CIO, CISO, and technology buyer. Decision-makers are always looking for insights on how to mitigate the security risks of implementing and using cloud solutions. Based on the presentation topics covered at the conference, as well as the general discussions heard between sessions, I wanted to share some of my observations on emerging trends. As cyber security serves as a fou...
Nov. 30, 2015 10:30 AM EST Reads: 361
With all the incredible momentum behind the Internet of Things (IoT) industry, it is easy to forget that not a single CEO wakes up and wonders if “my IoT is broken.” What they wonder is if they are making the right decisions to do all they can to increase revenue, decrease costs, and improve customer experience – effectively the same challenges they have always had in growing their business. The exciting thing about the IoT industry is now these decisions can be better, faster, and smarter. Now all corporate assets – people, objects, and spaces – can share information about themselves and thei...
Nov. 30, 2015 10:00 AM EST Reads: 303
The cloud. Like a comic book superhero, there seems to be no problem it can’t fix or cost it can’t slash. Yet making the transition is not always easy and production environments are still largely on premise. Taking some practical and sensible steps to reduce risk can also help provide a basis for a successful cloud transition. A plethora of surveys from the likes of IDG and Gartner show that more than 70 percent of enterprises have deployed at least one or more cloud application or workload. Yet a closer inspection at the data reveals less than half of these cloud projects involve production...
Nov. 30, 2015 09:00 AM EST Reads: 511
Discussions of cloud computing have evolved in recent years from a focus on specific types of cloud, to a world of hybrid cloud, and to a world dominated by the APIs that make today's multi-cloud environments and hybrid clouds possible. In this Power Panel at 17th Cloud Expo, moderated by Conference Chair Roger Strukhoff, panelists addressed the importance of customers being able to use the specific technologies they need, through environments and ecosystems that expose their APIs to make true change and transformation possible.
Nov. 30, 2015 08:00 AM EST Reads: 573
Microservices are a very exciting architectural approach that many organizations are looking to as a way to accelerate innovation. Microservices promise to allow teams to move away from monolithic "ball of mud" systems, but the reality is that, in the vast majority of organizations, different projects and technologies will continue to be developed at different speeds. How to handle the dependencies between these disparate systems with different iteration cycles? Consider the "canoncial problem" in this scenario: microservice A (releases daily) depends on a couple of additions to backend B (re...
Nov. 30, 2015 07:00 AM EST Reads: 479